STATS 2035

UWO

Course Overview

Lessons & Practice

I. Welcome

1. Collecting Data & Sampling

18min

1.1.1. Introduction to Statistics4 min

1.1.2. Sample vs. Population7 min

1.1.3. Practice

1.1.4. Measurement Scales7 min

1.1.5. Practice

2. Displaying (Graphing) Data

34min

2.1.1. Histograms4 min

2.1.2. Practice2 min

2.1.3. Practice2 min

2.1.4. Practice

2.2.1. Frequency Polygons2 min

2.2.2. Practice4 min

2.3.1. Stemplots (Stem-and-Leaf Plots)2 min

2.3.2. Practice3 min

2.4.1. Pie Chart3 min

2.4.2. Practice

2.5.1. Bar Chart3 min

2.5.2. Practice

2.6.1. Contingency Table (Two-Way Table)4 min

2.6.2. Practice

2.7.1. Scatterplots5 min

2.7.2. Practice

3. Measures of Center and Spread

1hr

3.1.1. Measures of Central Tendency7 min

3.1.2. Mean and Median Example2 min

3.1.3. Practice

3.1.4. Practice2 min

3.1.5. Practice3 min

3.2.1. Percentiles4 min

3.2.2. Example2 min

3.2.3. Practice

3.3.1. Range and Interquartile Range11 min

3.3.2. Variance and Standard Deviation6 min

3.3.3. Practice3 min

3.3.4. Practice3 min

3.3.5. Practice

3.4.1. Skewness and Symmetry 6 min

3.4.2. Practice

3.5.1. Boxplots and Five Number Summary9 min

3.5.2. Practice4 min

3.5.3. Practice

4. Probability

1.9hr

4.1.1. Events & Sample Spaces6 min

4.1.2. Types of Probability6 min

4.1.3. Probability Language & Notation4 min

4.1.4. Example3 min

4.1.5. Independent vs. Mutually Exclusive Events4 min

4.1.6. Example2 min

4.1.7. Practice

4.2.1. Venn Diagrams3 min

4.2.2. Tree Diagrams4 min

4.2.3. Two-way Table5 min

4.3.1. Interpretation of Probability2 min

4.3.2. Complement Rule3 min

4.3.3. Practice1 min

4.3.4. The Addition Rule4 min

4.4.1. Probability of Independent Events4 min

4.4.2. Example3 min

4.4.3. Practice2 min

4.5.1. Probability of Dependent Events (Conditional Probability)7 min

4.5.2. Conditional Probability: Tree Diagram5 min

4.5.3. Bayes’ Theorem4 min

4.5.4. Example4 min

4.5.5. Practice3 min

4.6.1. Example6 min

4.6.2. Example7 min

4.6.3. Example7 min

4.6.4. Practice4 min

4.6.5. Practice5 min

4.7.1. Summary of Key Definitions6 min

5. Counting Techniques

29min

5.1.1. Fundamental Counting Principle6 min

5.1.2. Permutations and Combinations6 min

5.1.3. Practice1 min

5.1.4. Practice54 sec

5.1.5. More Combination Rules3 min

5.1.6. Example4 min

5.1.7. Practice3 min

5.1.8. Practice

5.2.1. Counting and Probability3 min

5.2.3. Practice1 min

6. Discrete Random Variables

36min

6.1.1. Discrete Random Variables8 min

6.1.2. Probability Distribution Function4 min

6.1.3. Example4 min

6.1.4. Practice

6.1.5. Practice6 min

6.1.6. Pratice4 min

6.2.1. Expected Value, Variance, and Standard Deviation of Discrete Random Variables6 min

6.2.2. Example5 min

6.2.3. Practice

8. Continuous Probability Distributions

1.7hr

8.1.1. Continuous Probability Distribution Theory10 min

8.2.1. Uniform Distribution1 min

8.2.2. Practice3 min

8.3.1. Normal Distribution11 min

8.3.2. Practice5 min

8.4.1. Standard Normal Distribution (Z-Scores)11 min

8.4.2. Standardizing a Normal Random Variable4 min

8.4.3. Example10 min

8.4.4. Practice6 min

8.4.5. Practice3 min

8.5.1. Tchebysheff’s Theorem (Chebyshev's Theorem)3 min

8.5.2. Practice2 min

8.6.1. Normal Approximation to Binomial2 min

8.6.2. Practice5 min

8.6.3. Normal Approximation to the Binomial Distribution Question4 min

8.6.4. Normal Approximation to the Binomial Distribution Question4 min

8.7.1. Exponential Experiment3 min

8.7.2. Exponential Distribution7 min

8.7.3. Practice7 min

9. Sampling

26min

9.1.1. Statistical Sampling28 sec

9.1.2. Convenience Sampling1 min

9.1.3. Simple Random Sampling3 min

9.1.4. Systematic Sampling2 min

9.1.5. Stratified Sampling vs. Cluster Sampling6 min

9.1.6. Two-Stage Cluster Sampling2 min

9.1.7. Practice

9.1.8. Practice

9.1.9. Practice

9.2.1. Sampling Bias7 min

9.2.2. Recipe for a Good Sample5 min

9.2.3. Practice

9.2.4. Practice

10. Sampling Distribution

59min

10.1.1. Sampling Variability & Sampling Distribution12 min

10.2.1. Central Limit Theorem 5 min

10.2.2. Sampling Distribution for a Mean2 min

10.2.3. Example9 min

10.2.4. Sampling Distribution for a Mean Question5 min

10.3.1. Sampling Distribution of Proportions5 min

10.3.2. Example3 min

10.3.3. Sampling Distribution of Proportions4 min

10.4.1. Drawing Samples From a Finite Population8 min

10.4.2. Example4 min

10.4.3. Practice3 min

11. Confidence Intervals

48min

11.1.1. Introduction to Confidence Intervals14 min

11.2.1. Confidence Interval for a Mean13 min

11.2.2. Example4 min

11.2.3. Practice3 min

11.3.1. Confidence Interval for a Proportion2 min

11.3.2. Example5 min

11.3.3. Practice4 min

11.4.1. Margin of Error and Sample Size3 min

11.4.2. Practice

12. End of 1st Semester Topics/ Start of 2nd Semester Topics

12.1.1. End of 1st Semester Topics/ Start of 2nd Semester Topics

13. Hypothesis Testing

1.9hr

13.1.1. Introduction to Hypothesis Testing 15 min

13.1.2. Hypothesis Testing Steps25 min

13.2.1. Hypothesis Test for a Mean3 min

13.2.2. Example16 min

13.2.3. Example8 min

13.2.4. Practice4 min

13.3.1. Hypothesis Test for a Proportion10 min

13.3.2. Example4 min

13.3.3. Practice5 min

13.3.4. Practice9 min

13.4.1. Type I and Type II Errors5 min

13.4.2. Type I and Type II Errors1 min

13.4.3. Practice

13.4.4. Practice

13.4.5. Power7 min

13.4.6. Practice

14. Inference about a Population Variance

41min

14.1.1. Inference for Population Variance & Chi-square Distribution 8 min

14.2.1. Confidence Interval for Population Variance5 min

14.2.2. Example6 min

14.2.3. Pratice3 min

14.2.4. Practice

14.3.1. Hypothesis Test for Population Variance8 min

14.3.2. Example8 min

14.3.3. Hypothesis Test for Population Variance

14.3.4. Practice4 min

15. Inference for Two Population Means

1.6hr

15.1.1. Comparing Two Independent Means9 min

15.1.2. Hypothesis Test Steps: Comparing Two Independent Means11 min

15.2.1. Unpooled t-test (Unequal Variances)4 min

15.2.2. Example (Unpooled)11 min

15.2.3. Practice (Unpooled)5 min

15.3.1. Pooled t-test (Equal Variances)3 min

15.3.2. Example (Pooled)7 min

15.3.3. Practice (Pooled)7 min

15.4.1. Confidence Interval for Differences in Population Means (Pooled and Unpooled)6 min

15.4.2. Confidence Interval for Two Means Containing Zero7 min

15.4.3. Confidence Interval for Two Means (Independent Populations)9 min

15.5.1. Confidence Interval Unpooled t2 min

15.5.2. Example: Confidence Interval (Unpooled)5 min

15.5.3. Practice (Unpooled)

15.6.1. Confidence Interval Formula Pooled t2 min

15.6.2. Example: Confidence Interval w/ Pooled T-test5 min

15.6.3. Practice (Pooled)

16. Match Pairs (Dependent Means)

37min

16.1.1. Match Pairs for Dependent Means12 min

16.2.1. Hypothesis Test for Matched Pairs11 min

16.2.2. Example7 min

16.2.3. Practice3 min

16.3.1. Matched Pairs Confidence Interval for Differences in Two Dependent Population Means4 min

16.3.2. Practice

17. Inference for Two Population Proportions

49min

17.1.1. Hypothesis Testing for Two Independent Population Proportions9 min

17.1.2. Hypothesis Test Steps: Comparing Two Independent Proportions8 min

17.1.3. Example13 min

17.1.4. Practice (Pooled)6 min

17.2.1. Confidence Interval for Differences in Population Proportions3 min

17.2.2. Confidence Interval for Two Proportions1 min

17.2.3. Example4 min

17.2.4. Practice4 min

18. Test of Equality of Two Variances

35min

18.1.1. Test of Equality of Two Variances7 min

18.2.1. F-Test for Equality of Two Variances11 min

18.2.2. Example6 min

18.2.3. F-Test for Equality of Two Variances

18.3.1. Levene’s Test for the Equality of Two Variances4 min

18.3.2. Example7 min

18.3.3. Practice

19. Design of Experiments

11min

19.1.1. Types of Experimental Designs7 min

19.1.2. Principles of Experimental Design4 min

19.1.3. Example

19.1.4. Practice

19.1.5. Practice

20. One-Way ANOVA

38min

20.1.1. One-Way ANOVA8 min

20.1.2. One-Way ANOVA Table10 min

20.1.3. Example9 min

20.1.4. Practice

20.2.1. One-Way ANOVA Hypothesis Test6 min

20.2.2. Example4 min

20.2.3. Practice

20.3.1. Tukey’s Honest Significance Difference Multiple Comparison Method

20.3.2. Tukey’s Honest Significance Difference Multiple Comparison Method

21. Scatterplots, Association, and Correlation

37min

21.1.1. Scatterplots5 min

21.1.2. Practice

21.2.1. Correlation5 min

21.2.2. Practice

21.3.1. Solving for Correlation2 min

21.3.2. Example6 min

21.3.3. Practice4 min

21.3.4. Example3 min

21.3.5. Practice

21.4.1. Coefficient of Determination (R Squared)7 min

21.4.2. Assessing Goodness of Fit6 min

21.4.3. Practice

22. Simple Linear Regression

45min

22.1.1. Solving for the Regression Line (r, Sy, Sx Method)5 min

22.1.2. Example7 min

22.1.3. Practice (Version 1)3 min

22.1.4. Solving for the Regression Line (Least Squares Method)2 min

22.1.5. Example5 min

22.1.6. Practice (Version 2)5 min

22.2.1. Predictions3 min

22.2.2. Residuals (Errors)5 min

22.2.3. Practice

22.2.4. Residual Plots2 min

22.2.5. Regression Diagnostics 5 min

22.2.6. Practice

22.2.7. Standard Deviation of the Residuals5 min

22.2.8. Practice

23. Inference for Linear Regression

2.2hr

23.1.1. Estimating the Coefficients of the Linear Regression Model9 min

23.1.2. Measures of Variation in Regression9 min

23.1.3. Practice

23.2.1. Standard Error and R Square Formulas7 min

23.2.2. Example5 min

23.2.3. Practice4 min

23.3.1. Confidence Interval for Linear Regression5 min

23.3.2. Example9 min

23.3.3. Practice3 min

23.3.4. Slope: The Significance of "Zero" (or Lack Thereof)6 min

23.3.5. Practice

23.4.1. Hypothesis Testing for Linear Regression14 min

23.4.2. Example17 min

23.4.3. Example13 min

23.4.4. Practice: Linear Regression Analysis6 min

23.5.1. Prediction Interval of Y7 min

23.5.2. Example12 min

23.5.3. Practice10 min

23.5.4. Practice

24. Multiple Regression

1.7hr

24.1.1. Assessing a Multiple Regression Model5 min

24.1.2. F-test for Multiple Regression5 min

24.1.3. Solving for the F-score9 min

24.1.4. Example2 min

24.1.5. Practice8 min

24.2.1. Hypothesis Testing for Multiple Regression (F-test)7 min

24.2.2. Example26 min

24.2.3. Example13 min

24.2.4. Practice13 min

24.2.5. Practice12 min

25. Chi-Square

48min

25.1.1. Types of Chi Square Tests8 min

25.1.2. Chi-Square Test for "Goodness of Fit"4 min

25.1.3. Example7 min

25.1.4. Pratice9 min

25.1.5. Chi-Square Test for Independence5 min

25.1.6. Example8 min

25.1.7. Practice4 min

25.1.8. More on Chi-Square Tests3 min

Mock Exams

ME.1. Midterm 1 - Mock Assessment27 Qns

ME.2. Midterm 2 - Mock Assessment32 Qns

ME.3. Final Exam - Mock Assessment65 Qns

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Answered

Anonymous

hi, can you tell me which chapters are coming in our test (the prof said we had to cover chapters 1 to 5 with some part of 6 but the chapters overhear do not seem to cover the same topics thanks

L

Lawron L

Instructor

Hi Fahad. Are you referring to "Hypergeometric distributions"? It is listed in your syllabus. You should check with your TA or professor about what will actually be covered. If there are any missing topics not covered in Wize, please let me know. (I have credited you back 2 questions.)

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